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Quantification of soil is crucial for maximizing the advantages of land resources while minimizing the negative consequences of land degradation in the long term. It will also make it possible to identify locations that need immediate soil erosion management. The present study was carried out in the Kulfo river catchment, Rift valley, Southern Ethiopia. The Revised Universal Soil Loss Equation (RUSLE) method was utilized to estimate the mean yearly soil loss in the research region using remote sensing, other collateral data. The RUSLE model inputs were mapped and integrated into the ArcGIS software, and the results show that 0 and 1211 t ha−1year−1 are the minima and maximum soil loss in the present study area. Soil erosion-prone regions were divided into three categories: 0-42 t ha−1year−1 (low), 43-128 t ha−1 year−1 (medium), and > 128 t ha−1 year−1 (high). And the average rate of soil erosion is 68.47 t ha−1year−1. Low, medium, and high soil erosion areal extent and area percentages in the current research area is 270 km2 (77 %), 61 km2 (17 %), and 19 km2 (6%), respectively. A high rate of soil erosion was found where high steep slope, barren land, and high precipitation occurred in the present study area. The current study's outcomes were confirmed by comparing soil loss estimates in the same geo-environmental conditions found in Ethiopia's highlands. The outcome of this study is important for decision-makers and policymakers.

When groundwater quality is good, it may be a substantial water supply for various applications. However, no systematic research on hydrogeochemistry and water quality features for drinking and irrigation has been undertaken in the present study area. As a result, the current study looked at hydrogeochemical variables and groundwater quality for drinking and irrigation in Tercha district, Dawuro Zone, Southern Ethiopia. Forty-seven groundwater samples were collected and tested to satisfy the required target for various physicochemical properties. The hydrogeochemical features of the groundwater in the study region were assessed using in-situ testing and laboratory analysis of physicochemical parameters. Groundwater samples from the research region were slightly acidic to slightly basic, with the principal cations and anions decreasing in sequence: Na+ > Ca2+ > Mg2+ > K+ and HCO3-> Cl-> SO42-. The hadrochemical facies of the studied region evolved from mildly mineralized dominant highland Ca-HCO3 water types to moderately mineralized mixed Ca-Na-HCO3 water types to highly mineralized deep rift floor Na-HCO3 water types. Additionally, the World Health Organization and the Ethiopian Standard Agency were utilized to compare the drinking water quality. Except for NO3- (4.25 %), Fe (8.51 %), and F- (2.12%), all groundwater samples from the research region were determined to be within permitted limits and appropriate for drinking. According to the Water Quality Index, about 80.86% of groundwater samples are excellent, and 19.14% are good drinking water. Sodium absorption ratio (SAR), sodium (Na) percentage, residual sodium carbonate RSC, permeability index (PI), and magnesium hazard were among the irrigation water quality indicators calculated (MH). The great majority of groundwater samples are suitable for agricultural use.

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Groundwater is a vital natural resource that supports human needs, promotes industrial development, needs farming activities, and helps to maintain ecological balance. Geospatial technologies play an essential role in monitoring, assessing, and conserving groundwater resources. The present study was carried out at Arba Minch town, Rift Valley, southern Ethiopia. A total of eight important groundwater controlling parameters, such as lithology, geomorphology, lineament density, land-use/land cover, slope, precipitation, drainage density, and soil type, were considered to identify suitable groundwater potential zones. The analytical hierarchy process (AHP) technique was used to derive the standard weights for each parameter and its sub-parameters, emphasizing the relative importance of contributing parameters and sub-parameters for groundwater recharge. The present study’s potential groundwater zonation map was divided into three categories: poor, medium, and high. The output has shown about 36%, 24%, and 40% area falls under high, medium, and poor groundwater potential zones. Furthermore, the findings were validated using groundwater level data, which showed a strong correlation. The current study results showed the effect of geospatial techniques and the AHP method in groundwater potential mapping.